Ontology highlight
ABSTRACT:
PROVIDER: PRJNA980410 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR24860816.fastq.gz | Fastqsanger.gz | |||
| SRR24860817.fastq.gz | Fastqsanger.gz | |||
| SRR24860818.fastq.gz | Fastqsanger.gz | |||
| SRR24860819.fastq.gz | Fastqsanger.gz | |||
| SRR24860820.fastq.gz | Fastqsanger.gz |
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Project description:Sleeve gastrectomy (SG) can improve diabetes mellitus dramatically. However, the mechanisms remain largely undetermined. With the advancement of in-depth bioinformatic analysis, non-coding RNAs especially circular RNAs(circRNAs), have been implicated in many biological processes. To explore whether circRNAs mediate the amelioration of diabetes mellitus after SG, we subjected liver samples of diabetic rats after SG and shame operations for RNA sequencing. Through RNA sequencing, we identified a dramatically differentially expressed profile of 107 circRNAs. Some of these specific circRNAs were only expressed in diabetic rats after SG, which may be promising biological markers of SG prognosis.
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Project description:Sleeve gastrectomy (SG) could improve diabetes mellitus dramatically. However, the mechanisms remain largely undetermined. With the advancement of in-depth bioinformatic analysis, non-coding RNAs especially long non-coding RNAs(lncRNAs), have been implicated in many biological processes. To explore whether lncRNAs mediate the amelioration of diabetes mellitus condition after SG, we subjected liver samples of diabetic rats after SG and shame operations for RNA sequencing. Further, interaction network between lncRNAs and mRNAs/microRNAs(miRNAs) were constructed to infer the function of lncRNAs in diabetic remission, followed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses. Through RNA sequencing, we identified more than 9000 lncRNAs with a dramatically differentially expressed profile of 147 lncRNAs. Some of these specific lncRNAs were only expressed in diabetic rats after SG, which may be promising biological markers of diabetic remission and SG prognosis. Through co-analysis between lncRNAs and mRNAs, 20 potential target genes of lncRNAs were screened out. Further bioinformatic analysis indicated the differentially expressed lncRNAs harbored various miRNAs binding sites and three representative lncRNA-miRNA networks of lnc50 and lnc136 were constructed. The KEGG analysis revealed that differential expressed lncRNAs were mainly related to mitogen-activated protein kinase (MAPK) pathway. These results demonstrated that SG dramatically altered expression profile of lncRNAs on diabetes mellitus, and altered lncRNAs expression may contribute to the improvement on diabetic remission through MAPK pathway by interaction with mRNA/miRNA. Our findings provide valuable resources for molecular mechanism of diabetic remission after SG and is benefit for development of lncRNAs-based diagnostic and therapeutic interventions of diabetes mellitus.
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